Dentigerous Cyst and Glandular Odontogenic Cyst: A Rare Combination of Coexisting Pathologies.

A dentigerous cyst (DC) is the most common developmental cystic lesion of the jaws. Histologically, these cysts derive from the odontogenic epithelium that includes the reduced enamel epithelium, epithelial cell rests of Serres, and epithelial cell rests of Malassez. Radiographically, DCs are usually presented as well-defined radiolucencies associated with the crown of an unerupted tooth at the level of the cementoenamel junction (CEJ).

RNA Sequencing Experimental Analysis Workflow Using Caenorhabditis elegans.

RNA sequencing is an approach to transcriptomic profiling that enables the detection of differentially expressed genes in response to genetic mutation or experimental treatment, among other uses. Here we describe a method for the use of a customizable, user-friendly bioinformatic pipeline to identify differentially expressed genes in RNA sequencing data obtained from C. elegans, with attention to the improvement in reproducibility and accuracy of results.

Histopathologic evaluation of Asian-American patients with chronic rhinosinusitis with nasal polyps.

Asian-American (AA) patients with chronic rhinosinusitis with nasal polyps (CRSwNP) have comparable rates of tissue eosinophilia compared to Caucasians when defined as >10 eosinophils/high-powered field (HPF). AA patients with CRSwNP have significantly higher incidence of mixed inflammation defined as >10 eosinophils/HPF and >10 neutrophils/HPF.

Learning from virtual experiments to assist users of Small Angle Neutron Scattering in model selection.

In this work, we combine the advantages of virtual Small Angle Neutron Scattering (SANS) experiments carried out by Monte Carlo simulations with the recent advances in computer vision to generate a tool that can assist SANS users in small angle scattering model selection. We generate a dataset of almost 260.000 SANS virtual experiments of the SANS beamline KWS-1 at FRM-II, Germany, intended for Machine Learning purposes.

Protocol for the selection of spontaneous resistant mutants to d-cycloserine.

(MTB) is known for its adaptive capability in developing resistance to antibiotics, through the selection of spontaneous mutations that arise during treatment. Generating spontaneous antibiotic-resistant mutants is challenging but necessary for studying this phenomenon. A protocol was designed and tested to select stable, MTB spontaneous, d-cycloserine (DCS) resistant mutants.